Abstract
Recent years have seen a worsening in the decline of honey bees (Apis mellifera L.) colonies. This phenomenon has sparked a great amount of attention regarding the need for intense bee hive monitoring, in order to identify possible causes, and design corresponding countermeasures. Honey bees have a key role in pollination services of both cultivated and spontaneous flora, and the increase in bee mortality could lead to an ecological and economical damage. Despite many smart monitoring systems for honey bees and bee hives, relying on different sensors and measured quantities, have been proposed over the years, the most promising ones are based on sound analysis. Sounds are used by the bees to communicate within the hive, and their analysis can reveal useful information to understand the colony health status and to detect sudden variations, just by using a simple microphone and an acquisition system. The work here presented aims to provide a review of the most interesting approaches proposed over the years for honey bees sound analysis and the type of knowledge about bees that can be extracted from sounds.
Highlights
Among insects, honey bees are well known for their positive effects on a multitude of different scopes
Mel Frequency Cepstral Coefficients (MFCC) is a widely known technique for signal representation, in which the coefficients are generated starting from the square of signal spectrogram; a triangular filterbank is applied to the signal; the Discrete Cosine Transform (DCT) is applied to the logarithmic output of the filterbank
Regarding Hilbert–Huang Transform (HHT), the features extraction technique is based on a combination of two algorithms, i.e., the Empirical Mode Decomposition (EMD), which decomposes the signal into a set of basis functions, and the Hilbert Transform (HT) which transforms each basis function into a time-frequency representation of the signal
Summary
Honey bees are well known for their positive effects on a multitude of different scopes. Large bee mortality can result in a loss of pollination services with negative ecological and economic [5] impacts that could significantly affect the maintenance of wild plant diversity, wider ecosystem stability and crop production [6,7]. Solutions such as robotic pollination were proposed in recent years, but they were already shown to be technically and economically unacceptable solutions, currently posing substantial ecological and ethical risks [8]. The necessity of a continuous and intensive monitoring of bee hives’ status emerges clearly, in order to safeguard and protect these important insects
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